Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears the full burden of behavioral disclosure, yet it says nothing about read-only vs. mutating behavior, authentication requirements, rate limits, or what happens on an invalid tweet_id. A single noun phrase conveys no behavioral context at all.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short with zero wasted words, so it is concise by default. But it is a fragment rather than a front-loaded sentence, and its brevity stems from under-specification rather than disciplined editing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations, no output schema, and a required identifier parameter, the agent needs to know what is returned, whether auth is required, and what errors look like. The description supplies none of this, leaving it incomplete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (tweet_id and the optional _token fallback auth) are already documented in the schema, including the recommended HTTP header alternative. The description adds nothing beyond that, which is the expected baseline when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The phrase 'Twitter/X推文详情' identifies the platform (Twitter/X) and the resource (a tweet's details), which does disambiguate the cryptic name 'tw_post' among non-Twitter siblings. However, it is a bare noun phrase with no verb and only the vague word 'details', so it does not state what operation is performed or what the details contain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool, no prerequisites, and no mention of alternatives (e.g. comment-fetching siblings like weibo_comments or ig_post). The agent must infer usage entirely from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.